The current invention is broadly related to power amplifiers and more specifically, to predistortion techniques used to compensate for memoryless and memory effects associated with power amplifiers.
Power amplifiers are used in communication systems to amplify communication signals before they are transmitted. Every power amplifier has an associated amplitude gain and phase shift characteristics. An ideal power amplifier has a constant gain and introduces constant delay (that is linear phase shift with frequency) at its output over the entire range of input signal values.
In practice, however, power amplifiers deviate from the ideal behavior described above. A non-ideal power amplifier introduces distortion effects in the output signal. The distortion effects are characterized as memoryless and memory effects. The memoryless effects include non-constant amplitude gain and non-constant phase shift introduced by the power amplifier.
The memory effects arise because even the nonlinear effect of the power amplifier is not constant with time. Thus, the same input signal gives different output signals at different times. The distortion effects introduced by a power amplifier are not constant and change with time due to temperature changes, voltage variations, bias changes, aging and the like. These non-constant distortion effects are responsible for introduction of the memory effects in the output signals.
To eliminate the above-mentioned distortion effects in a signal, the signal is predistorted. Predistortion is distorting the signal before it enters the power amplifier so that the memoryless and memory effects introduced by the power amplifier are cancelled or, at least, reduced.
Predistorting the input signal with the inverse of memoryless effects involves insertion of a nonlinear module between the input signal and the power amplifier so that the overall characteristics of the nonlinear module and the power amplifier are similar to that of a linear memoryless power amplifier.
To reduce the memory effects in a signal, it is important for the predistortion system to adapt to the dynamic changes that occur in the power amplifier. Compensation for the dynamic changes in the power amplifier can be achieved through a feedback loop in the predistortion system. The feedback loop enables the predistortion system to adapt to the changes in the characteristics of the power amplifier.
The first step in predistortion involves estimation of the magnitude of the distortion effects introduced in a signal by a power amplifier. Then, the input signal is predistorted by an inverse of the estimated distortion effects. Subsequently, the predistorted signal is passed through the power amplifier. The predistorted input signal has reduced distortion effects after amplification due to the neutralization of the distortion effects.
There are two types of techniques existing in the art for predistortion of communication signals, memoryless predistortion techniques and memory-based predistortion techniques.
Memoryless predistortion techniques reduce the memoryless effects in the amplified communication signal. However, these techniques are not able to eliminate memory effects.
Memory-based predistortion techniques are capable of eliminating the memory effects in addition to the memoryless effects. Therefore, memory-based predistortion techniques are more effective in removing distortion effects introduced by a power amplifier than memoryless predistortion techniques.
Some patents that disclose methods for carrying out memory-based predistortion are discussed hereinafter.
WIPO patent application number 01/05026 A1 titled “A Wideband Digital Predistortion Linearizer for Nonlinear Amplifiers”, assigned to Datum Telegraphic, Inc., Vancouver, British Columbia, Canada, discloses a digital compensation signal processing (DCSP) component. The DCSP component predistorts an input transmission signal to compensate for the frequency and time dependent distortion characteristics of a nonlinear amplifier. The DCSP component comprises a data structure for storing compensation parameters. New compensation parameters are added for every signal sample being predistorted according to the last compensation parameters stored in the DCSP component.
Another U.S. Pat. No. 6,587,514 B1 titled “Digital Pre-distortion Methods for Wideband Amplifiers”, assigned to PMC-Sierra, Inc., Santa Clara, Calif., USA, discloses a predistortion system that compensates for a nonlinear amplifier's frequency and time dependent distortion characteristics. Various sets of compensation parameters are generated periodically and written to a data structure by an adaptive processing component. The adaptive processing component performs a non-real time analysis of amplifier input and output signals to generate compensation parameters.
Further, a WIPO patent application number 02/095932 A1 titled “Digitally Implemented Predistorter Control Mechanism for Linearizing High Efficiency RF Power Amplifiers”, assigned to Spectrian Corporation, Sunnyvale, Calif., USA discloses a digital signal processor. The digital signal processor uses two signal processing operators to carry out predistortion. The first signal processing operator represents an inverse of the dynamic memory effects in the nonlinear transfer characteristic of the amplifier. The second signal processing operator represents an inverse of static nonlinearities in the transfer characteristic of the amplifier. These two signal operators are used to eliminate nonlinearities and memory effects from the amplified signal.
Finally, a WIPO patent application number 03/043183 A1 titled “Digital Linearization Circuit”, assigned to Telefonaktiebolaget Lm Ericsson, Stockholm, Sweden discloses a solution for minimizing distortion characteristics due to power amplifiers, including memory effects. The solution is based on adaptive nonlinear performance observations. The physical cause for the distortion is compensated for in the application. A predistorter digital circuit is derived that has an inverse functionality of the digital device model to eliminate the distortion effects.
However, a drawback in the above-mentioned predistortion techniques is that they are computationally intensive. The complexity of computations is introduced by the method of calculating and implementing the inverse of the memory effects, which is required to reduce the said memory effects.
Therefore, keeping the above discussion into perspective, there is a need for a memory-based predistortion technique that eliminates memory effects in a computationally efficient way.